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Exploring Functional Connectivity Networks in fMRI Data Using Clustering Analysis

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Brain Informatics (BI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6889))

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Abstract

Some approaches have been proposed for exploring functional brain connectivity networks from functional magnetic resonance imaging (fMRI) data. Based on a popular algorithm K-means and an effective clustering algorithm called Affinity Propagation (AP), a combined clustering method to explore the functional brain connectivity networks is presented. In the proposed method, K-means is used for data reduction and AP is used for clustering. Without setting the seed of ROI in advance, the proposed method is especially appropriate for the analysis of fMRI data collected with a periodic experimental paradigm. The validity of the proposed method is illustrated by experiments on a simulated dataset and a human dataset. Receiver operating characteristic (ROC) analysis was performed on the simulated dataset. Results show that this method can efficiently and robustly detect the actual functional response with typical signal changes in the aspect of noise ratio, phase and amplitude. On the human dataset, the proposed method discovered brain networks which are compatible with the findings of previous studies.

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Author information

Authors and Affiliations

  1. International WIC Institute, Beijing University of Technology, Beijing, China

    Dazhong Liu, Ning Zhong & Yulin Qin

  2. School of Mathematics and Computer Science, Hebei University, Baoding, China

    Dazhong Liu

  3. Dept. of Life Science and Informatics, Maebashi Institute of Technology, Maebashi, Japan

    Ning Zhong

Authors
  1. Dazhong Liu
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  2. Ning Zhong
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  3. Yulin Qin
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Editor information

Editors and Affiliations

  1. School of Information Science and Engineering, Feiyun Lou Building, Lanzhou University, Tianshui South Road 222, 730000, Lanzhou, Gansu, China

    Bin Hu

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR

    Jiming Liu

  3. Chinese Academy of Sciences, Institute of Biophysics, 15 Datun Road, Chaoyng District, 100101, Beijing, China

    Lin Chen

  4. Department of Life Science and Informatics, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, 371.0816, Maebashi-City, Japan

    Ning Zhong

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© 2011 Springer-Verlag Berlin Heidelberg

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Liu, D., Zhong, N., Qin, Y. (2011). Exploring Functional Connectivity Networks in fMRI Data Using Clustering Analysis. In: Hu, B., Liu, J., Chen, L., Zhong, N. (eds) Brain Informatics. BI 2011. Lecture Notes in Computer Science(), vol 6889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23605-1_17

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  • DOI: https://doi.org/10.1007/978-3-642-23605-1_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23604-4

  • Online ISBN: 978-3-642-23605-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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